DNA methylome profiling of human tissues identifies global and tissue-specific methylation patterns

Global DNA methylation is not elevated in blood samples from Machado-Joseph disease mutation carriers

Machado-Joseph disease (MJD) is an autosomal dominant spinocerebellar ataxia (SCA) caused by a polyglutamine expansion in the ataxin-3 protein, which initiates a cascade of pathogenic events, including transcriptional dysregulation. Genotype-phenotype correlations in MJD are incomplete, suggesting an influence of additional factors, such as epigenetic modifications, underlying the MJD pathogenesis. DNA methylation is known to impact the pathophysiology of neurodegenerative disorders through gene expression regulation and increased methylation has been reported for other SCAs. In this work we aimed to analyse global methylation in MJD carriers. Global 5-mC levels were quantified in blood samples of 33 MJD mutation carriers (patients and preclinical subjects) and 33 healthy controls, matched by age, sex, and smoking status. For a subset of 16 MJD subjects, a pilot follow-up analysis with two time points was also conducted. No differences were found in median global 5-mC levels between MJD mutation carriers and controls and no correlations between methylation levels and clinical or genetic variables were detected. Also, no alterations in global 5-mC levels were observed over time. Our findings do not support an increase in global blood methylation levels associated with MJD.

Grandmotherhood is associated with reduced OXTR DNA methylation

In mammals, both parental and alloparental care are associated with increased brain oxytocin signaling. Grandmothers are important alloparents in many human families. Based on animal model research showing that peripheral Oxtr methylation is associated with Oxtr expression in the nucleus accumbens, we investigated whether grandmaternal caregiving is associated with lower peripheral OXTR methylation. Results reveal several regions within OXTR where grandmothers have lower DNA methylation compared with non-grandmother controls, and no regions where grandmothers have higher OXTR DNA methylation. Among grandmothers, OXTR methylation was most strongly correlated with the grandmother's assessment of the degree of positive feelings between her and the grandchild, which in turn predicted caregiving engagement. Although there was little evidence that grandmaternal OXTR methylation modulated grandmaternal neural responses to viewing photos of the grandchild within brain regions involved in caregiving motivation, it was negatively correlated with the neural response to an unknown grandchild. Thus, while OT signaling may not be essential for activating grandmaternal brain reward systems in our low-stress experimental context, it may support caregiving motivation towards unrelated children. Future longitudinal research should determine whether the transition to grandmotherhood is associated with a reduction in OXTR methylation.

Novel PAX3::MAML3 fusion identified in alveolar rhabdomyosarcoma, using DNA methylation profiling to expand the genetic spectrum of "fusion-positive" cases

Alveolar rhabdomyosarcoma (ARMS) with FOXO1 gene rearrangements is an aggressive pediatric rhabdomyosarcoma subtype that is prognostically distinct from embryonal rhabdomyosarcoma and fusion-negative ARMS. Herein, we report two cases of ARMS with PAX3::MAML3 fusions. The tumors arose in an infant and an adolescent as stage IV metastatic disease (by Children's Oncology Group staging system). Histologically, both cases were small round blue cell tumors arranged in vague nests and solid sheets that were diffusely positive for desmin and myogenin. By methylation profiling and unsupervised clustering analysis, the tumors clustered with ARMS with classic FOXO1 rearrangements and ARMS with variant PAX3::NCOA1/INO80D fusions, but not with biphenotypic sinonasal sarcoma (BSNS) with PAX3::MAML3/NCOA2/FOXO1/YAP1 fusions, nor with other small round blue cell tumors, including embryonal rhabdomyosarcoma. The differentially methylated genes between ARMS and BSNS were highly enriched in genes involved in myogenesis, and 21% of these genes overlap with target genes of the PAX3::FOXO1 fusion transcription factor. On follow-up after initiation of vincristine/actinomycin/cyclophosphamide chemotherapy, the tumors showed partial and complete clinical response, consistent with typical upfront chemotherapy responsiveness of ARMS with the classic FOXO1 rearrangement. We conclude that PAX3::MAML3 is a novel variant fusion of ARMS, which displays a methylation signature distinct from BSNS despite sharing similar PAX3 fusions. These findings highlight the utility of methylation profiling in classifying ARMS with non-canonical fusions.

Exposure to elevated glucocorticoid during development primes altered transcriptional responses to acute stress in adulthood

Early life stress (ELS) is a major risk factor for developing psychiatric disorders, with glucocorticoids (GCs) implicated in mediating its effects in shaping adult phenotypes. In this process, exposure to high levels of developmental GC (hdGC) is thought to induce molecular changes that prime differential adult responses. However, identities of molecules targeted by hdGC exposure are not completely known. Here, we describe lifelong molecular consequences of hdGC exposure using a newly developed zebrafish double-hit stress model, which shows altered behaviors and stress hypersensitivity in adulthood. We identify a set of primed genes displaying altered expression only upon acute stress in hdGC-exposed adult fish brains. Interestingly, this gene set is enriched in risk factors for psychiatric disorders in humans. Lastly, we identify altered epigenetic regulatory elements following hdGC exposure. Thus, our study provides comprehensive datasets delineating potential molecular targets mediating the impact of hdGC exposure on adult responses.

Epigenome-wide association studies identify novel DNA methylation sites associated with PTSD: A meta-analysis of 23 military and civilian cohorts

Background

The occurrence of post-traumatic stress disorder (PTSD) following a traumatic event is associated with biological differences that can represent the susceptibility to PTSD, the impact of trauma, or the sequelae of PTSD itself. These effects include differences in DNA methylation (DNAm), an important form of epigenetic gene regulation, at multiple CpG loci across the genome. Moreover, these effects can be shared or specific to both central and peripheral tissues. Here, we aim to identify blood DNAm differences associated with PTSD and characterize the underlying biological mechanisms by examining the extent to which they mirror associations across multiple brain regions.

Methods

As the Psychiatric Genomics Consortium (PGC) PTSD Epigenetics Workgroup, we conducted the largest cross-sectional meta-analysis of epigenome-wide association studies (EWASs) of PTSD to date, involving 5077 participants (2156 PTSD cases and 2921 trauma-exposed controls) from 23 civilian and military studies. PTSD diagnosis assessments were harmonized following the standardized guidelines established by the PGC-PTSD Workgroup. DNAm was assayed from blood using either Illumina HumanMethylation450 or MethylationEPIC (850K) BeadChips. A common QC pipeline was applied. Within each cohort, DNA methylation was regressed on PTSD, sex (if applicable), age, blood cell proportions, and ancestry. An inverse variance-weighted meta-analysis was performed. We conducted replication analyses in tissue from multiple brain regions, neuronal nuclei, and a cellular model of prolonged stress.

Results

We identified 11 CpG sites associated with PTSD in the overall meta-analysis (1.44e-09 < p < 5.30e-08), as well as 14 associated in analyses of specific strata (military vs civilian cohort, sex, and ancestry), including CpGs in AHRR and CDC42BPB . Many of these loci exhibit blood-brain correlation in methylation levels and cross-tissue associations with PTSD in multiple brain regions. Methylation at most CpGs correlated with their annotated gene expression levels.

Conclusions

This study identifies 11 PTSD-associated CpGs, also leverages data from postmortem brain samples, GWAS, and genome-wide expression data to interpret the biology underlying these associations and prioritize genes whose regulation differs in those with PTSD.

Map of epigenetic age acceleration: A worldwide analysis

We present a systematic analysis of epigenetic age acceleration based on by far the largest collection of publicly available DNA methylation data for healthy samples (93 datasets, 23 K samples), focusing on the geographic (25 countries) and ethnic (31 ethnicities) aspects around the world. We employed the most popular epigenetic tools for assessing age acceleration and examined their quality metrics and ability to extrapolate to epigenetic data from different tissue types and age ranges different from the training data of these models. In most cases, the models proved to be inconsistent with each other and showed different signs of age acceleration, with the PhenoAge model tending to systematically underestimate and different versions of the GrimAge model tending to systematically overestimate the age prediction of healthy subjects. Referring to data availability and consistency, most countries and populations are still not represented in GEO, moreover, different datasets use different criteria for determining healthy controls. Because of this, it is difficult to fully isolate the contribution of "geography/environment", "ethnicity" and "healthiness" to epigenetic age acceleration. Among the explored metrics, only the DunedinPACE, which measures aging rate, appears to adequately reflect the standard of living and socioeconomic indicators in countries, although it has a limited application to blood methylation data only. Invariably, by epigenetic age acceleration, males age faster than females in most of the studied countries and populations.

Sex-related DNA methylation is associated with inflammation and gene expression in the lungs of healthy individuals

Lung cancer exhibits sex-biased molecular characteristics and epidemiological trends, suggesting a need for sex-specific approaches to understanding its etiology and treatment. DNA methylation alterations play critical roles in lung carcinogenesis and may serve as valuable biomarkers for precision medicine strategies. We employed the Infinium MethylationEPIC array to identify autosomal sex-related differentially methylated CpG sites (DM-CpGs) in lung epithelium of healthy individuals (32 females and 37 males) while controlling for age, BMI, and tobacco use. We correlated DM-CpGs with gene expression in lung epithelium and immune responses in bronchoalveolar lavage. We validated these DM-CpGs in lung tumors and adjacent normal tissue from The Cancer Genome Atlas (TCGA). Among 522 identified DM-CpGs, 61% were hypermethylated in females, predominantly located in promoter regions. These DM genes were implicated in cell-to-cell signaling, cellular function, transport, and lipid metabolism. Correlation analysis revealed sex-specific patterns between DM-CpGs and gene expression. Additionally, several DM-CpGs were correlated significantly with cytokines (IL-1β, IL-4, IL-12p70, and IFN-γ), macrophage, and lymphocyte counts. Also, some DM-CpGs were observed in TCGA lung adenocarcinoma, squamous cell carcinoma, and adjacent normal tissues. Our findings highlight sex-specific DNA methylation patterns in healthy lung epithelium and their associations with lung gene expression and lung immune biomarkers. These findings underscore the potential role of lung sex-related CpGs as epigenetic predispositions influencing sex disparities in lung cancer risk and outcomes, warranting further investigation for personalized lung cancer management strategies.

Molecular adaptations in response to exercise training are associated with tissue-specific transcriptomic and epigenomic signatures

Regular exercise has many physical and brain health benefits, yet the molecular mechanisms mediating exercise effects across tissues remain poorly understood. Here we analyzed 400 high-quality DNA methylation, ATAC-seq, and RNA-seq datasets from eight tissues from control and endurance exercise-trained (EET) rats. Integration of baseline datasets mapped the gene location dependence of epigenetic control features and identified differing regulatory landscapes in each tissue. The transcriptional responses to 8 weeks of EET showed little overlap across tissues and predominantly comprised tissue-type enriched genes. We identified sex differences in the transcriptomic and epigenomic changes induced by EET. However, the sex-biased gene responses were linked to shared signaling pathways. We found that many G protein-coupled receptor-encoding genes are regulated by EET, suggesting a role for these receptors in mediating the molecular adaptations to training across tissues. Our findings provide new insights into the mechanisms underlying EET-induced health benefits across organs.

Methods for the Analysis of Multiple Epigenomic Mediators in Environmental Epidemiology

PURPOSE OF REVIEW

Epigenetic changes can be highly influenced by environmental factors and have in turn been proposed to influence chronic disease. Being able to quantify to which extent epigenomic processes are mediators of the association between environmental exposures and diseases is of interest for epidemiologic research. In this review, we summarize the proposed mediation analysis methods with applications to epigenomic data.

RECENT FINDINGS

The ultra-high dimensionality and high correlations that characterize omics data have hindered the precise quantification of mediated effects. Several methods have been proposed to deal with mediation in high-dimensional settings, including methods that incorporate dimensionality reduction techniques to the mediation algorithm. Although important methodological advances have been conducted in the previous years, key challenges such as the development of sensitivity analyses, dealing with mediator-mediator interactions, including environmental mixtures as exposures, or the integration of different omic data should be the focus of future methodological developments for epigenomic mediation analysis.

DNA methylation in necrotizing enterocolitis

Epigenetic modifications, such as DNA methylation, are enzymatically regulated processes that directly impact gene expression patterns. In early life, they are central to developmental programming and have also been implicated in regulating inflammatory responses. Research into the role of epigenetics in neonatal health is limited, but there is a growing body of literature related to the role of DNA methylation patterns and diseases of prematurity, such as the intestinal disease necrotizing enterocolitis (NEC). NEC is a severe intestinal inflammatory disease, but the key factors that precede disease development remain to be determined. This knowledge gap has led to a failure to design effective targeted therapies and identify specific biomarkers of disease. Recent literature has identified altered DNA methylation patterns in the stool and intestinal tissue of neonates with NEC. These findings provide the foundation for a new avenue in NEC research. In this review, we will provide a general overview of DNA methylation and then specifically discuss the recent literature related to methylation patterns in neonates with NEC. We will also discuss how DNA methylation is used as a biomarker for other disease states and how, with further research, methylation patterns may serve as potential biomarkers for NEC.

Can DNA Methylation Profiling Classify Histologic Subtypes and Grades in Soft Tissue Sarcoma?

BACKGROUND

A clear classification of the subtype and grade of soft tissue sarcoma is important for predicting prognosis and establishing treatment strategies. However, the rarity and heterogeneity of these tumors often make diagnosis difficult. In addition, it remains challenging to predict the response to chemotherapy and prognosis. Thus, we need a new method to help diagnose soft tissue sarcomas and determine treatment strategies in conjunction with traditional methods. Genetic alterations can be found in some subtypes of soft tissue sarcoma, but many other types show dysregulated gene expression attributed to epigenetic changes, such as DNA methylation status. However, research on DNA methylation profiles in soft tissue sarcoma is still insufficient to provide information to assist in diagnosis and therapeutic decisions.

QUESTIONS/PURPOSES

(1) Do DNA methylation profiles differ between normal tissue and soft tissue sarcoma? (2) Do DNA methylation profiles vary between different histologic subtypes of soft tissue sarcoma? (3) Do DNA methylation profiles differ based on tumor grade?

METHODS

Between January 2019 and December 2022, we treated 85 patients for soft tissue sarcomas. We considered patients whose specimens were approved for pilot research by the Human Biobank of St. Vincent's Hospital, The Catholic University of Korea, as potentially eligible. Based on this, 41% (35 patients) were eligible; 1% (one patient) was excluded because of gender mismatch between clinical and genetic data after controlling for data quality. Finally, 39 specimens (34 soft tissue sarcomas and five normal samples) were included from 34 patients who had clinical data. All tissue samples were collected intraoperatively. The five normal tissue samples were from muscle tissues. There were 20 female patients and 14 male patients, with a median age of 58 years (range 19 to 82 years). Genomic DNA was extracted from frozen tissue, and DNA methylation profiles were obtained. Genomic annotation of DNA methylation sites and hierarchical cluster analysis were performed to interpret results from DNA methylation profiling. A t-test was used to analyze different methylation probes. Benjamini-Hochberg-adjusted p value calculations were used to account for bias resulting from evaluating thousands of methylation sites.

RESULTS

The most common histologic subtypes were liposarcoma (n = 10) and leiomyosarcoma (n = 9). The tumor grade was Fédération Nationale des Centres de Lutte Contre Le Cancer Grades 1, 2, and 3 in 3, 15, and 16 patients, respectively. DNA methylation profiling demonstrated differences between soft tissue sarcoma and normal tissue as 21,188 cytosine-phosphate-guanine sites. Despite the small number of samples, 72 of these sites showed an adjusted p value of < 0.000001, suggesting a low probability of statistical errors. Among the 72 sites, 70 exhibited a hypermethylation pattern in soft tissue sarcoma, with only two sites showing a hypomethylation pattern. Thirty of 34 soft tissue sarcomas were distinguished from normal samples using hierarchical cluster analysis. There was a different methylation pattern between leiomyosarcoma and liposarcoma at 7445 sites. Using the data, hierarchical clustering analysis showed that liposarcoma was distinguished from leiomyosarcoma. When we used the same approach and included other subtypes with three or more samples, only leiomyosarcoma and myxofibrosarcoma were separated from the other subtypes, while liposarcoma and alveolar soft-part sarcoma were mixed with the others. When comparing DNA methylation profiles between low-grade (Grade 1) and high-grade (Grades 2 and 3) soft tissue sarcomas, a difference in methylation pattern was observed at 144 cytosine-phosphate-guanine sites. Among these, 132 cytosine-phosphate-guanine sites exhibited hypermethylation in the high-grade group compared with the low-grade group. Hierarchical clustering analysis showed a division into two groups, with most high-grade sarcomas (28 of 31) separated from the low-grade group and few (3 out of 31) clustered together with the low-grade group. However, three high-grade soft tissue sarcomas were grouped with the Grade 1 cluster, and all of these sarcomas were Grade 2. When comparing Grades 1 and 2 to Grade 3, Grade 3 tumors were separated from Grades 1 and 2.

CONCLUSION

We observed a different DNA methylation pattern between soft tissue sarcomas and normal tissues. Liposarcoma was distinguished from leiomyosarcoma using methylation profiling. High-grade soft tissue sarcoma samples showed a hypermethylation pattern compared with low-grade ones. Our findings indicate the need for research using methylation profiling to better understand the diverse biological characteristics of soft tissue sarcoma. Such research should include studies with sufficient samples and a variety of subtypes, as well as analyses of the expression and function of related genes. Additionally, efforts to link this research with clinical data related to treatment and prognosis are necessary.

LEVEL OF EVIDENCE

Level III, diagnostic study.

BNIP3 and DAPK1 methylation in peripheral blood leucocytes are noninvasive biomarkers for gastric cancer

OBJECTIVE

The objective of this study is to comprehensively investigate the potential value of BNIP3 and DAPK1 methylation in peripheral blood leukocytes as a non-invasive biomarker for the detection of gastric cancer (GC), prediction of chemotherapy efficacy, and prognosis assessment.

PATIENTS AND METHODS

Initially, multiple bioinformatic analyses were employed to explore the genetic landscape and biological effects of BNIP3 and DAPK1 in GC tissues. Subsequently, case-control and prospective follow-up studies were conducted to compare the differences in BNIP3 and DAPK1 methylation levels in peripheral blood leukocytes among GC patients and healthy controls, as well as between patients exhibiting sensitivity and resistance to platinum plus fluorouracil treatment, and between patients with varying survival outcomes of GC. Additionally, several predictive nomograms were constructed based on the identified CpG sites and relevant clinical parameters to forecast the occurrence of GC, chemotherapy efficacy, and prognosis.

RESULTS

The upregulation of BNIP3 and DAPK1 was found to be associated with the development and poorer survival outcomes of GC. Furthermore, the expression of BNIP3/DAPK1 exhibited an inverse relationship with their DNA methylation levels and demonstrated a positive correlation with immune cell infiltration, as well as the IC50 values of 5-Fluorouracil and Cisplatin in GC tissues. Increased infiltration of macrophages in the high-expression groups was observed to be linked to unfavorable GC survival. In the case-control and follow-up studies, lower methylation levels of BNIP3 and DAPK1 were identified in the peripheral leukocytes of GC patients compared to healthy controls. Hypomethylation was also associated with more aggressive subtypes, diminished chemotherapy efficacy, and poorer survival outcomes in GC.

CONCLUSION

The DNA methylation of BNIP3 and DAPK1 in peripheral blood leukocytes holds promise as a novel non-invasive biomarker for predicting the occurrence of GC, chemotherapy efficacy, and prognosis assessment.

Distinctive cell-free DNA methylation characterizes presymptomatic genetic frontotemporal dementia

OBJECTIVE

Methylation of plasma cell-free DNA (cfDNA) has potential as a marker of brain damage in neurodegenerative diseases such as frontotemporal dementia (FTD). Here, we study methylation of cfDNA in presymptomatic and symptomatic carriers of genetic FTD pathogenic variants, next to healthy controls.

METHODS

cfDNA was isolated from cross-sectional plasma of 10 presymptomatic carriers (4 C9orf72, 4 GRN, and 2 MAPT), 10 symptomatic carriers (4 C9orf72, 4 GRN, and 2 MAPT), and 9 healthy controls. Genome-wide methylation of cfDNA was determined using a high-resolution sequencing technique (MeD-seq). Cumulative scores based on the identified differentially methylated regions (DMRs) were estimated for presymptomatic carriers (vs. controls and symptomatic carriers), and reevaluated in a validation cohort (8 presymptomatic: 3 C9orf72, 3 GRN, and 2 MAPT; 26 symptomatic: 7 C9orf72, 6 GRN, 12 MAPT, and 1 TARDBP; 13 noncarriers from genetic FTD families).

RESULTS

Presymptomatic carriers showed a distinctive methylation profile compared to healthy controls and symptomatic carriers. Cumulative DMR scores in presymptomatic carriers enabled to significantly differentiate presymptomatic carriers from healthy controls (p < 0.001) and symptomatic carriers (p < 0.001). In the validation cohort, these scores differentiated presymptomatic carriers from symptomatic carriers (p ≤ 0.007) only. Transcription-start-site methylation in presymptomatic carriers, generally associated with gene downregulation, was enriched for genes involved in ubiquitin-dependent processes, while gene body methylation, generally associated with gene upregulation, was enriched for genes involved in neuronal cell processes.

INTERPRETATION

A distinctive methylation profile of cfDNA characterizes the presymptomatic stage of genetic FTD, and could reflect neuronal death in this stage.

Biological aging markers in blood and brain tissue indicate age acceleration in alcohol use disorder

BACKGROUND

Alcohol use disorder (AUD) is associated with increased mortality and morbidity risk. A reason for this could be accelerated biological aging, which is strongly influenced by disease processes such as inflammation. As recent studies of AUD show changes in DNA methylation and gene expression in neuroinflammation-related pathways in the brain, biological aging represents a potentially important construct for understanding the adverse effects of substance use disorders. Epigenetic clocks have shown accelerated aging in blood samples from individuals with AUD. However, no systematic evaluation of biological age measures in AUD across different tissues and brain regions has been undertaken.

METHODS

As markers of biological aging (BioAge markers), we assessed Levine's and Horvath's epigenetic clocks, DNA methylation telomere length (DNAmTL), telomere length (TL), and mitochondrial DNA copy number (mtDNAcn) in postmortem brain samples from Brodmann Area 9 (BA9), caudate nucleus, and ventral striatum (N = 63-94), and in whole blood samples (N = 179) of individuals with and without AUD. To evaluate the association between AUD status and BioAge markers, we performed linear regression analyses while adjusting for covariates.

RESULTS

The majority of BioAge markers were significantly associated with chronological age in all samples. Levine's epigenetic clock and DNAmTL were indicative of accelerated biological aging in AUD in BA9 and whole blood samples, while Horvath's showed the opposite effect in BA9. No significant association of AUD with TL and mtDNAcn was detected. Measured TL and DNAmTL showed only small correlations in blood and none in brain.

CONCLUSIONS

The present study is the first to simultaneously investigate epigenetic clocks, telomere length, and mtDNAcn in postmortem brain and whole blood samples in individuals with AUD. We found evidence for accelerated biological aging in AUD in blood and brain, as measured by Levine's epigenetic clock, and DNAmTL. Additional studies of different tissues from the same individuals are needed to draw valid conclusions about the congruence of biological aging in blood and brain.

Mixed Patterns of Intergenerational DNA Methylation Inheritance in Acropora

For sessile organisms at high risk from climate change, phenotypic plasticity can be critical to rapid acclimation. Epigenetic markers like DNA methylation are hypothesized as mediators of plasticity; methylation is associated with the regulation of gene expression, can change in response to ecological cues, and is a proposed basis for the inheritance of acquired traits. Within reef-building corals, gene-body methylation (gbM) can change in response to ecological stressors. If coral DNA methylation is transmissible across generations, this could potentially facilitate rapid acclimation to environmental change. We investigated methylation heritability in Acropora, a stony reef-building coral. Two Acropora millepora and two Acropora selago adults were crossed, producing eight offspring crosses (four hybrid, two of each species). We used whole-genome bisulfite sequencing to identify methylated loci and allele-specific alignments to quantify per-locus inheritance. If methylation is heritable, differential methylation (DM) between the parents should equal DM between paired offspring alleles at a given locus. We found a mixture of heritable and nonheritable loci, with heritable portions ranging from 44% to 90% among crosses. gBM was more heritable than intergenic methylation, and most loci had a consistent degree of heritability between crosses (i.e. the deviation between parental and offspring DM were of similar magnitude and direction). Our results provide evidence that coral methylation can be inherited but that heritability is heterogenous throughout the genome. Future investigations into this heterogeneity and its phenotypic implications will be important to understanding the potential capability of intergenerational environmental acclimation in reef building corals.

Toward Explainable Artificial Intelligence for Precision Pathology

The rapid development of precision medicine in recent years has started to challenge diagnostic pathology with respect to its ability to analyze histological images and increasingly large molecular profiling data in a quantitative, integrative, and standardized way. Artificial intelligence (AI) and, more precisely, deep learning technologies have recently demonstrated the potential to facilitate complex data analysis tasks, including clinical, histological, and molecular data for disease classification; tissue biomarker quantification; and clinical outcome prediction. This review provides a general introduction to AI and describes recent developments with a focus on applications in diagnostic pathology and beyond. We explain limitations including the black-box character of conventional AI and describe solutions to make machine learning decisions more transparent with so-called explainable AI. The purpose of the review is to foster a mutual understanding of both the biomedical and the AI side. To that end, in addition to providing an overview of the relevant foundations in pathology and machine learning, we present worked-through examples for a better practical understanding of what AI can achieve and how it should be done.

Creation and Validation of the First Infinium DNA Methylation Array for the Human Imprintome

Background

Differentially methylated imprint control regions (ICRs) regulate the monoallelic expression of imprinted genes. Their epigenetic dysregulation by environmental exposures throughout life results in the formation of common chronic diseases. Unfortunately, existing Infinium methylation arrays lack the ability to profile these regions adequately. Whole genome bisulfite sequencing (WGBS) is the unique method able to profile these regions, but it is very expensive and it requires not only a high coverage but it is also computationally intensive to assess those regions.

Findings

To address this deficiency, we developed a custom methylation array containing 22,819 probes. Among them, 9,757 probes map to 1,088 out of the 1,488 candidate ICRs recently described. To assess the performance of the array, we created matched samples processed with the Human Imprintome array and WGBS, which is the current standard method for assessing the methylation of the Human Imprintome. We compared the methylation levels from the shared CpG sites and obtained a mean R 2 = 0.569. We also created matched samples processed with the Human Imprintome array and the Infinium Methylation EPIC v2 array and obtained a mean R 2 = 0.796. Furthermore, replication experiments demonstrated high reliability (ICC: 0.799-0.945).

Conclusions

Our custom array will be useful for replicable and accurate assessment, mechanistic insight, and targeted investigation of ICRs. This tool should accelerate the discovery of ICRs associated with a wide range of diseases and exposures, and advance our understanding of genomic imprinting and its relevance in development and disease formation throughout the life course.

Metabolic and immune costs balance during natural acclimation of corals in fluctuating environments

Epigenetic modifications based on DNA methylation can rapidly improve the potential of corals to adapt to environmental pressures by increasing their phenotypic plasticity, a factor important for scleractinian corals to adapt to future global warming. However, the extent to which corals develop similar adaptive mechanisms and their specific adaptation processes remain unclear. Here, to reveal the regulatory mechanism by which DNA methylation improves thermal tolerance in Pocillopora damicornis under fluctuating environments, we analyzed genome-wide DNA methylation signatures in P. damicornis and compared the differences in the methylation and transcriptional responses of P. damicornis from fluctuating and stable environments using whole-genome bisulfite sequencing and nanopore-based RNA sequencingtranscriptome sequencing. We discovered low methylation levels in P. damicornis (average methylation 4.14%), with CpG accounting for 74.88%, CHH for 13.27%, and CHG for 11.85% of this methylation. However, methylation levels did not change between coral samples from the fluctuating and stable environments. The varied methylation levels in different regions of the gene revealed that the overall methylation level of the gene body was relatively high and showed a bimodal methylation pattern. Methylation occurs primarily in exons rather than introns within the gene body In P. damicornis, there was only a weak correlation between methylation and transcriptional changes at the individual gene level, and the methylation and gene expression levels generally exhibited a bell-shaped relationship, which we speculate may be due to the specificity of cnidarian species. Correlation analysis between methylation levels and the transcriptome revealed that the highest proportion of the top 20 enriched KEGG pathways was related to immunity. Additionally, P. damicornis collected from a high-temperature pool had a lower metabolic rate than those collected from a low-temperature pool. We hypothesize that the dynamic balance of energy-expenditure costs between immunity and metabolism is an important strategy for increasing P. damicornis tolerance. The fluctuating environment of high-temperature pools may increase the heat tolerance in corals by increasing their immunity and thus lowering their metabolism.

Alterations to DNA methylation patterns induced by chemotherapy treatment are associated with negative impacts on the olfactory pathway

BACKGROUND

Exposure to cytotoxic chemotherapy treatment may alter DNA methylation (DNAm) in breast cancer patients.

METHODS

We performed DNAm analysis in 125 breast cancer patients with blood drawn before and after chemotherapy, using the Illumina MethylationEPIC array. DNAm changes of 588,798 individual CpGs (including 41,207 promoter regions) were evaluated using linear regression models adjusted for monocyte proportion. Gene set enrichment analyses (GSEA) were conducted to identify key Gene Ontology (GO) biological processes or Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with chemotherapy. Results were validated in a separate cohort of breast cancer patients who were treated (n = 1273) and not treated (n = 872) by chemotherapy (1808 blood, 337 saliva).

RESULTS

A total of 141 differentially methylated CpGs and 11 promoters were significantly associated with chemotherapy after multiple testing corrections in both the paired sample and single time point analyses. GSEA of promoter regions (pre-ranked by test statistics) identified six suppressed biological processes (p < 4.67e-8) related to sensory perception and detection of chemical stimuli, including smell perception (GO:0007606, GO:0007608, GO:0009593, GO:0050906, GO:0050907, and GO:0050911). The same six biological processes were significantly suppressed in the validation dataset (p < 9.02e-14). The KEGG pathway olfactory transduction (hsa04740) was also found to be significantly suppressed (ppaired-samples = 1.72e-9, psingle-timepoint-blood = 2.03e-15 and psingle-timepoint-saliva = 7.52e-56).

CONCLUSION

The enrichment of imprinted genes within biological processes and pathways suggests a biological mechanism by which chemotherapy could affect the perception of smell.

Rapid and visual detection of specific bacteria for saliva and vaginal fluid identification with the lateral flow dipstick strategy

Identification of body fluids is critical for crime scene reconstruction, and a source of investigation source of investigative leads. In recent years, microbial DNA analysis using sequencing and quantitative real-time polymerase chain reaction have been used to identify body fluids. However, these techniques are time-consuming, expensive, and require complex workflows. In this study, a new method for simultaneous detection of Streptococcus salivarius and Lactobacillus crispatus using polymerase chain reaction (PCR) in combination with a lateral flow dipstick (LFD) was developed to identify saliva and vaginal fluid in forensic samples. LFD results can be observed with the naked eye within 3 min with a sensitivity of 0.001 ng/µL DNA. The PCR-LFD assay was successfully used to detect S. salivarius and L. crispatus in saliva and vaginal fluid respectively, and showed negative results in blood, semen, nasal fluid, and skin. Moreover, saliva and vaginal fluid were detectable even at an extremely high mixing ratio of sample DNA (1:999). Saliva and vaginal fluid were identified in various mock forensic samples. These results indicate that saliva and vaginal fluid can be effectively detected by identifying S. salivarius and L. crispatus, respectively. Furthermore, we have shown that DNA samples used to identify saliva and vaginal fluid can also provide a complete short tandem repeat (STR) profile when used as source material for forensic STR profiling. In summary, our results suggest that PCR-LFD is a promising assay for rapid, simple, reliable, and efficient identification of body fluids.

Genetic and Epigenetic Regulation in Lingo-1: Effects on Cognitive Function and White Matter Microstructure in a Case-Control Study for Schizophrenia

Leucine-rich repeat and immunoglobulin domain-containing protein (Lingo-1) plays a vital role in a large number of neuronal processes underlying learning and memory, which are known to be disrupted in schizophrenia. However, Lingo-1 has never been examined in the context of schizophrenia. The genetic association of a single-nucleotide polymorphism (SNP, rs3144) and methylation (CpG sites) in the Lingo-1 3'-UTR region was examined, with the testing of cognitive dysfunction and white matter (WM) integrity in a schizophrenia case-control cohort (n = 268/group). A large subset of subjects (97 control and 161 schizophrenia subjects) underwent structural magnetic resonance imaging (MRI) brain scans to assess WM integrity. Frequency of the rs3144 minor allele was overrepresented in the schizophrenia population (p = 0.03), with an odds ratio of 1.39 (95% CI 1.016-1.901). CpG sites surrounding rs3144 were hypermethylated in the control population (p = 0.032) compared to the schizophrenia group. rs3144 genotype was predictive of membership to a subclass of schizophrenia subjects with generalized cognitive deficits (p < 0.05), in addition to having associations with WM integrity (p = 0.018). This is the first study reporting a potential implication of genetic and epigenetic risk factors in Lingo-1 in schizophrenia. Both of these genetic and epigenetic alterations may also have associations with cognitive dysfunction and WM integrity in the context of the schizophrenia pathophysiology.

Comparative computational analysis to distinguish mesenchymal stem cells from fibroblasts

Introduction

Mesenchymal stem cells (MSCs) are considered to be the most promising stem cell type for cell-based therapies in regenerative medicine. Based on their potential to home to diseased body sites following a therapeutically application, these cells could (i) differentiate then into organ-specific cell types to locally restore injured cells or, most prominently, (ii) foster tissue regeneration including immune modulations more indirectly by secretion of protective growth factors and cytokines. As tissue-resident stem cells of mesenchymal origin, these cells are morphologically and even molecularly- at least concerning the classical marker genes- indistinguishable from similar lineage cells, particularly fibroblasts.

Methods

Here we used microarray-based gene expression and global DNA methylation analyses as well as accompanying computational tools in order to specify differences between MSCs and fibroblasts, to further unravel potential identity genes and to highlight MSC signaling pathways with regard to their trophic and immunosuppressive action.

Results

We identified 1352 differentially expressed genes, of which in the MSCs there is a strong signature for e.g., KRAS signaling, known to play essential role in stemness maintenance, regulation of coagulation and complement being decisive for resolving inflammatory processes, as well as of wound healing particularly important for their regenerative capacity. Genes upregulated in fibroblasts addressed predominately transcription and biosynthetic processes and mapped morphological features of the tissue. Concerning the cellular identity, we specified the already known HOX code for MSCs, established a potential HOX code for fibroblasts, and linked certain HOX genes to functional cell-type-specific properties. Accompanied methylation profiles revealed numerous regions, especially in HOX genes, being differentially methylated, which might provide additional biomarker potential.

Discussion

Conclusively, transcriptomic together with epigenetic signatures can be successfully be used for the definition (cellular identity) of MSCs versus fibroblasts as well as for the determination of the superior functional properties of MSCs, such as their immunomodulatory potential.

DNA methylation profiling to determine the primary sites of metastatic cancers using formalin-fixed paraffin-embedded tissues

Identifying the primary site of metastatic cancer is critical to guiding the subsequent treatment. Approximately 3-9% of metastatic patients are diagnosed with cancer of unknown primary sites (CUP) even after a comprehensive diagnostic workup. However, a widely accepted molecular test is still not available. Here, we report a method that applies formalin-fixed, paraffin-embedded tissues to construct reduced representation bisulfite sequencing libraries (FFPE-RRBS). We then generate and systematically evaluate 28 molecular classifiers, built on four DNA methylation scoring methods and seven machine learning approaches, using the RRBS library dataset of 498 fresh-frozen tumor tissues from primary cancer patients. Among these classifiers, the beta value-based linear support vector (BELIVE) performs the best, achieving overall accuracies of 81-93% for identifying the primary sites in 215 metastatic patients using top-k predictions (k = 1, 2, 3). Coincidentally, BELIVE also successfully predicts the tissue of origin in 81-93% of CUP patients (n = 68).

Comprehensive tissue deconvolution of cell-free DNA by deep learning for disease diagnosis and monitoring

Plasma cell-free DNA (cfDNA) is a noninvasive biomarker for cell death of all organs. Deciphering the tissue origin of cfDNA can reveal abnormal cell death because of diseases, which has great clinical potential in disease detection and monitoring. Despite the great promise, the sensitive and accurate quantification of tissue-derived cfDNA remains challenging to existing methods due to the limited characterization of tissue methylation and the reliance on unsupervised methods. To fully exploit the clinical potential of tissue-derived cfDNA, here we present one of the largest comprehensive and high-resolution methylation atlas based on 521 noncancer tissue samples spanning 29 major types of human tissues. We systematically identified fragment-level tissue-specific methylation patterns and extensively validated them in orthogonal datasets. Based on the rich tissue methylation atlas, we develop the first supervised tissue deconvolution approach, a deep-learning-powered model, cfSort, for sensitive and accurate tissue deconvolution in cfDNA. On the benchmarking data, cfSort showed superior sensitivity and accuracy compared to the existing methods. We further demonstrated the clinical utilities of cfSort with two potential applications: aiding disease diagnosis and monitoring treatment side effects. The tissue-derived cfDNA fraction estimated from cfSort reflected the clinical outcomes of the patients. In summary, the tissue methylation atlas and cfSort enhanced the performance of tissue deconvolution in cfDNA, thus facilitating cfDNA-based disease detection and longitudinal treatment monitoring.

Hypermethylated GRIA4, a potential biomarker for an early non-invasive detection of metastasis of clinically known colorectal cancer

Introduction

Colorectal cancer (CRC) can develop through several dysregulated molecular pathways, including the serrated pathway, characterized by CpG island methylator (CIMP) phenotype. Although the tumor tissue is a commonly tested material, sample types such as stool or plasma, bring a new, non-invasive approach. Several cancer-related methylated genes have been identified in CRC patients, including gene GRIA4, showing promising diagnostic potential. The aim of our study was to develop a sensitive droplet digital PCR (ddPCR) assay to examine GRIA4 hypermethylation status in CRC patients and evaluate its diagnostic potential in tissue and liquid biopsy samples.

Methods

In total, 23 patients participated in this study, 7 patients with primary CRC and 16 patients with liver metastasis of clinically known CRC. We obtained tumor and non-tumor tissues (N=17), blood samples pre- and post-surgery (N=22), and blood of five volunteers without a personal cancer history. We have developed and optimized a ddPCR assay for GRIA4 hypermethylation detection, from tissue and plasma samples.

Results

We detected significantly increased GRIA4 methylation in tumor tissues compared to their adjacent non-tumor tissue, p<0.0001. Receiver operating characteristic (ROC) analysis defined cutoff values to separate primary tumors and metastases from non-tumor colon/rectum, specifically 36.85% for primary tumors and 34.81% for metastases. All primary tumors were above this threshold. When comparing the methylation levels of metastatic vs. non-tumor tissue, a smaller increase was observed in liver metastasis versus colon tissue (3.6× gain; p=0.001), then in liver metastasis versus adjacent liver tissue (17.4× gain; p<0.0001). On average, GRIA4 hypermethylation in primary tumor plasma was 2.8-fold higher (p=0.39), and in metastatic plasma, 16.4-fold higher (p=0.0011) compared to healthy individuals. Hypermethylation in metastatic plasma was on average 5.9 times higher (p=0.051) than in primary tumor plasma. After tumor removal surgery, average hypermethylation decrease in plasma was 1.6× for primary (p=0.037) and 4.5× for metastatic patients (p=0.023).

Discussion

Based on our data, it can be inferred that GRIA4 serves as a tissue specific biomarker for the colon/rectum tissue, thus is suitable for cancer classification. This biomarker showed the potential to be an attractive target for early non-invasive detection of metastases of clinically known CRC, although additional analysis has to be performed.

Meg8-DMR as the Secondary Regulatory Region Regulates the Expression of MicroRNAs While It Does Not Affect Embryonic Development in Mice

Meg8-DMR is the first maternal methylated DMR to be discovered in the imprinted Dlk1-Dio3 domain. The deletion of Meg8-DMR enhances the migration and invasion of MLTC-1 depending on the CTCF binding sites. However, the biological function of Meg8-DMR during mouse development remains unknown. In this study, a CRISPR/Cas9 system was used to generate 434 bp genomic deletions of Meg8-DMR in mice. High-throughput and bioinformatics profiling revealed that Meg8-DMR is involved in the regulation of microRNA: when the deletion was inherited from the mother (Mat-KO), the expression of microRNA was unchanged. However, when the deletion occurred from the father (Pat-KO) and homozygous (Homo-KO), the expression was upregulated. Then, differentially expressed microRNAs (DEGs) were identified between WT with Pat-KO, Mat-KO, and Homo-KO, respectively. Subsequently, these DEGs were subjected to the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) term enrichment analysis to explore the functional roles of these genes. In total, 502, 128, and 165 DEGs were determined. GO analysis showed that these DEGs were mainly enriched in axonogenesis in Pat-KO and Home-KO, while forebrain development was enriched in Mat-KO. Finally, the methylation levels of IG-DMR, Gtl2-DMR, and Meg8-DMR, and the imprinting status of Dlk1, Gtl2, and Rian were not affected. These findings suggest that Meg8-DMR, as a secondary regulatory region, could regulate the expression of microRNAs while not affecting the normal embryonic development of mice.

Comparative analysis reveals epigenomic evolution related to species traits and genomic imprinting in mammals

DNA methylation is an epigenetic modification that plays a crucial role in various regulatory processes, including gene expression regulation, transposable element repression, and genomic imprinting. However, most studies on DNA methylation have been conducted in humans and other model species, whereas the dynamics of DNA methylation across mammals remain poorly explored, limiting our understanding of epigenomic evolution in mammals and the evolutionary impacts of conserved and lineage-specific DNA methylation. Here, we generated and gathered comparative epigenomic data from 13 mammalian species, including two marsupial species, to demonstrate that DNA methylation plays critical roles in several aspects of gene evolution and species trait evolution. We found that the species-specific DNA methylation of promoters and noncoding elements correlates with species-specific traits such as body patterning, indicating that DNA methylation might help establish or maintain interspecies differences in gene regulation that shape phenotypes. For a broader view, we investigated the evolutionary histories of 88 known imprinting control regions across mammals to identify their evolutionary origins. By analyzing the features of known and newly identified potential imprints in all studied mammals, we found that genomic imprinting may function in embryonic development through the binding of specific transcription factors. Our findings show that DNA methylation and the complex interaction between the genome and epigenome have a significant impact on mammalian evolution, suggesting that evolutionary epigenomics should be incorporated to develop a unified evolutionary theory.

Distinguishable DNA methylation defines a cardiac-specific epigenetic clock

BACKGROUND

The present study investigates whether epigenetic differences emerge in the heart of patients undergoing cardiac surgery for an aortic valvular replacement (AVR) or coronary artery bypass graft (CABG). An algorithm is also established to determine how the pathophysiological condition might influence the human biological cardiac age.

RESULTS

Blood samples and cardiac auricles were collected from patients who underwent cardiac procedures: 94 AVR and 289 CABG. The CpGs from three independent blood-derived biological clocks were selected to design a new blood- and the first cardiac-specific clocks. Specifically, 31 CpGs from six age-related genes, ELOVL2, EDARADD, ITGA2B, ASPA, PDE4C, and FHL2, were used to construct the tissue-tailored clocks. The best-fitting variables were combined to define new cardiac- and blood-tailored clocks validated through neural network analysis and elastic regression. In addition, telomere length (TL) was measured by qPCR. These new methods revealed a similarity between chronological and biological age in the blood and heart; the average TL was significantly higher in the heart than in the blood. In addition, the cardiac clock discriminated well between AVR and CABG and was sensitive to cardiovascular risk factors such as obesity and smoking. Moreover, the cardiac-specific clock identified an AVR patient's subgroup whose accelerated bioage correlated with the altered ventricular parameters, including left ventricular diastolic and systolic volume.

CONCLUSION

This study reports on applying a method to evaluate the cardiac biological age revealing epigenetic features that separate subgroups of AVR and CABG.

Shifting the Cancer Screening Paradigm: The Rising Potential of Blood-Based Multi-Cancer Early Detection Tests

Cancer remains a leading cause of death worldwide, partly owing to late detection which entails limited and often ineffective therapeutic options. Most cancers lack validated screening procedures, and the ones available disclose several drawbacks, leading to low patient compliance and unnecessary workups, adding up the costs to healthcare systems. Hence, there is a great need for innovative, accurate, and minimally invasive tools for early cancer detection. In recent years, multi-cancer early detection (MCED) tests emerged as a promising screening tool, combining molecular analysis of tumor-related markers present in body fluids with artificial intelligence to simultaneously detect a variety of cancers and further discriminate the underlying cancer type. Herein, we aim to provide a highlight of the variety of strategies currently under development concerning MCED, as well as the major factors which are preventing clinical implementation. Although MCED tests depict great potential for clinical application, large-scale clinical validation studies are still lacking.

Unveiling the epigenomic mechanisms of acquired platinum-resistance in high-grade serous ovarian cancer

Resistance to platinum-based chemotherapy is the major cause of death from high-grade serous ovarian cancer (HGSOC). We hypothesise that detection of specific DNA methylation changes may predict platinum resistance in HGSOC. Using a publicly available "discovery" dataset we examined epigenomic and transcriptomic alterations between primary platinum-sensitive (n = 32) and recurrent acquired drug resistant HGSOC (n = 28) and identified several genes involved in immune and chemoresistance-related pathways. Validation via high-resolution melt analysis of these findings, in cell lines and HGSOC tumours, demonstrated the most consistent changes were observed in three of the genes: APOBEC3A, NKAPL and PDCD1. Plasma samples from an independent HGSOC cohort (n = 17) were analysed using droplet digital PCR. Hypermethylation of NKAPL was detected in 46% and hypomethylation of APOBEC3A in 69% of plasma samples taken from women with relapsed HGSOC (n = 13), with no alterations identified in disease-free patients (n = 4). Following these results, and using a CRISPR-Cas9 approach, we were also able to demonstrate that in vitro NKAPL promoter demethylation increased platinum sensitivity by 15%. Overall, this study demonstrates the importance of aberrant methylation, especially of the NKAPL gene, in acquired platinum resistance in HGSOC.

In individuals with Williams syndrome, dysregulation of methylation in non-coding regions of neuronal and oligodendrocyte DNA is associated with pathology and cortical development

Williams syndrome (WS) is a neurodevelopmental disorder caused by a heterozygous micro-deletion in the WS critical region (WSCR) and is characterized by hyper-sociability and neurocognitive abnormalities. Nonetheless, whether and to what extent WSCR deletion leads to epigenetic modifications in the brain and induces pathological outcomes remains largely unknown. By examining DNA methylation in frontal cortex, we revealed genome-wide disruption in the methylome of individuals with WS, as compared to typically developed (TD) controls. Surprisingly, differentially methylated sites were predominantly annotated as introns and intergenic loci and were found to be highly enriched around binding sites for transcription factors that regulate neuronal development, plasticity and cognition. Moreover, by utilizing enhancer-promoter interactome data, we confirmed that most of these loci function as active enhancers in the human brain or as target genes of transcriptional networks associated with myelination, oligodendrocyte (OL) differentiation, cognition and social behavior. Cell type-specific methylation analysis revealed aberrant patterns in the methylation of active enhancers in neurons and OLs, and important neuron-glia interactions that might be impaired in individuals with WS. Finally, comparison of methylation profiles from blood samples of individuals with WS and healthy controls, along with other data collected in this study, identified putative targets of endophenotypes associated with WS, which can be used to define brain-risk loci for WS outside the WSCR locus, as well as for other associated pathologies. In conclusion, our study illuminates the brain methylome landscape of individuals with WS and sheds light on how these aberrations might be involved in social behavior and physiological abnormalities. By extension, these results may lead to better diagnostics and more refined therapeutic targets for WS.

CpG methylation patterns in placenta and neonatal blood are differentially associated with neonatal inflammation

BACKGROUND

Infants born extremely premature are at increased risk for health complications later in life for which neonatal inflammation may be a contributing biological driver. Placental CpG methylation provides mechanistic information regarding the relationship between prenatal epigenetic programming, prematurity, neonatal inflammation, and later-in-life health.

METHODS

We contrasted CpG methylation in the placenta and neonatal blood spots in relation to neonatal inflammation in the Extremely Low Gestational Age Newborn (ELGAN) cohort. Neonatal inflammation status was based on the expression of six inflammation-related proteins, assessed as (1) day-one inflammation (DOI) or (2) intermittent or sustained systemic inflammation (ISSI, inflammation on ≥2 days in the first 2 postnatal weeks). Epigenome-wide CpG methylation was assessed in 354 placental samples and 318 neonatal blood samples.

RESULTS

Placental CpG methylation displayed the strongest association with ISSI (48 CpG sites) but was not associated with DOI. This was in contrast to CpG methylation in blood spots, which was associated with DOI (111 CpG sites) and not with ISSI (one CpG site).

CONCLUSIONS

Placental CpG methylation was strongly associated with ISSI, a measure of inflammation previously linked to later-in-life cognitive impairment, while day-one neonatal blood methylation was associated with DOI.

IMPACT

Neonatal inflammation increases the risk of adverse later-life outcomes, especially in infants born extremely preterm. CpG methylation in the placenta and neonatal blood spots were evaluated in relation to neonatal inflammation assessed via circulating proteins as either (i) day-one inflammation (DOI) or (ii) intermittent or sustained systemic inflammation (ISSI, inflammation on ≥2 days in the first 2 weeks). Tissue specificity was observed in epigenetic-inflammatory relationships: placental CpG methylation was associated with ISSI, neonatal blood CpG methylation was associated with DOI. Supporting the placental origins of disease framework, placental epigenetic patterns are associated with a propensity for ISSI in neonates.

The impact of epigenetic mechanisms in migraine: Current knowledge and future directions

BACKGROUND

Epigenetic mechanisms, including DNA methylation, microRNAs and histone modifications, may modulate the genetic expression in migraine and its interaction with internal and external factors, such as lifestyle and environmental changes.

OBJECTIVE

To summarize, contextualize and critically analyze the published literature on the current state of epigenetic mechanisms in migraine in a narrative review.

FINDINGS

The studies published to date have used different approaches and methodologies to determine the role of epigenetic mechanisms in migraine. Epigenetic changes seem to be involved in migraine and are increasing our knowledge of the disease.

CONCLUSIONS

Changes in DNA methylation, microRNA expression and histone modifications could be utilized as biomarkers that would be highly valuable for patient stratification, molecular diagnosis, and precision medicine in migraine.

Cervical Secretion Methylation Is Associated with the Pregnancy Outcome of Frozen-Thawed Embryo Transfer

The causes of implantation failure remain a black box in reproductive medicine. The exact mechanism behind the regulation of endometrial receptivity is still unknown. Epigenetic modifications influence gene expression patterns and may alter the receptivity of human endometrium. Cervical secretions contain endometrial genetic material, which can be used as an indicator of the endometrial condition. This study evaluates the association between the cervical secretion gene methylation profile and pregnancy outcome in a frozen-thawed embryonic transfer (FET) cycle. Cervical secretions were collected from women who entered the FET cycle with a blastocyst transfer (36 pregnant and 36 non-pregnant women). The DNA methylation profiles of six candidate genes selected from the literature review were measured by quantitative methylation-specific PCR (qMSP). Bioinformatic analysis of six selected candidate genes showed significant differences in DNA methylation between receptive and pre-receptive endometrium. All candidate genes showed different degrees of correlation with the pregnancy outcomes in the logistic regression model. A machine learning approach showed that the combination of candidate genes' DNA methylation profiles could differentiate pregnant from non-pregnant samples with an accuracy as high as 86.67% and an AUC of 0.81. This study demonstrated the association between cervical secretion methylation profiles and pregnancy outcomes in an FET cycle and provides a basis for potential clinical application as a non-invasive method for implantation prediction.

Multi-omic association study identifies DNA methylation-mediated genotype and smoking exposure effects on lung function in children living in urban settings

Impaired lung function in early life is associated with the subsequent development of chronic respiratory disease. Most genetic associations with lung function have been identified in adults of European descent and therefore may not represent those most relevant to pediatric populations and populations of different ancestries. In this study, we performed genome-wide association analyses of lung function in a multiethnic cohort of children (n = 1,035) living in low-income urban neighborhoods. We identified one novel locus at the TDRD9 gene in chromosome 14q32.33 associated with percent predicted forced expiratory volume in one second (FEV1) (p = 2.4x10-9; βz = -0.31, 95% CI = -0.41- -0.21). Mendelian randomization and mediation analyses revealed that this genetic effect on FEV1 was partially mediated by DNA methylation levels at this locus in airway epithelial cells, which were also associated with environmental tobacco smoke exposure (p = 0.015). Promoter-enhancer interactions in airway epithelial cells revealed chromatin interaction loops between FEV1-associated variants in TDRD9 and the promoter region of the PPP1R13B gene, a stimulator of p53-mediated apoptosis. Expression of PPP1R13B in airway epithelial cells was significantly associated the FEV1 risk alleles (p = 1.3x10-5; β = 0.12, 95% CI = 0.06-0.17). These combined results highlight a potential novel mechanism for reduced lung function in urban youth resulting from both genetics and smoking exposure.

MC profiling: a novel approach to analyze DNA methylation heterogeneity in genome-wide bisulfite sequencing data

DNA methylation is an epigenetic mark implicated in crucial biological processes. Most of the knowledge about DNA methylation is based on bulk experiments, in which DNA methylation of genomic regions is reported as average methylation. However, average methylation does not inform on how methylated cytosines are distributed in each single DNA molecule. Here, we propose Methylation Class (MC) profiling as a genome-wide approach to the study of DNA methylation heterogeneity from bulk bisulfite sequencing experiments. The proposed approach is built on the concept of MCs, groups of DNA molecules sharing the same number of methylated cytosines. The relative abundances of MCs from sequencing reads incorporates the information on the average methylation, and directly informs on the methylation level of each molecule. By applying our approach to publicly available bisulfite-sequencing datasets, we individuated cell-to-cell differences as the prevalent contributor to methylation heterogeneity. Moreover, we individuated signatures of loci undergoing imprinting and X-inactivation, and highlighted differences between the two processes. When applying MC profiling to compare different conditions, we identified methylation changes occurring in regions with almost constant average methylation. Altogether, our results indicate that MC profiling can provide useful insights on the epigenetic status and its evolution at multiple genomic regions.

DNA methylation-based classification of sinonasal tumors

The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply a machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, one class composed of highly aggressive SMARCB1-deficient carcinomas and another class with tumors that represent potentially previously misclassified adenoid cystic carcinomas. Our findings can aid in improving the diagnostic classification of sinonasal tumors and could help to change the current perception of SNUCs.

Single-Cell Dissection of the Multiomic Landscape of High-Grade Serous Ovarian Cancer

High-grade serous cancer (HGSC) is the most common subtype of ovarian cancer. HGSC is highly aggressive with poor patient outcomes, and a deeper understanding of HGSC tumorigenesis could help guide future treatment development. To systematically characterize the underlying pathologic mechanisms and intratumoral heterogeneity in human HGSC, we used an optimized single-cell multiomics sequencing technology to simultaneously analyze somatic copy-number alterations (SCNA), DNA methylation, chromatin accessibility, and transcriptome in individual cancer cells. Genes associated with interferon signaling, metallothioneins, and metabolism were commonly upregulated in ovarian cancer cells. Integrated multiomics analyses revealed that upregulation of interferon signaling and metallothioneins was influenced by both demethylation of their promoters and hypomethylation of satellites and LINE1, and potential key transcription factors regulating glycolysis using chromatin accessibility data were uncovered. In addition, gene expression and DNA methylation displayed similar patterns in matched primary and abdominal metastatic tumor cells of the same genetic lineage, suggesting that metastatic cells potentially preexist in the subclones of primary tumors. Finally, the lineages of cancer cells with higher residual DNA methylation levels and upregulated expression of CCN1 and HSP90AA1 presented greater metastatic potential. This study characterizes the critical genetic, epigenetic, and transcriptomic features and their mutual regulatory relationships in ovarian cancer, providing valuable resources for identifying new molecular mechanisms and potential therapeutic targets for HGSC.

SIGNIFICANCE

Integrated analysis of multiomic changes and epigenetic regulation in high-grade serous ovarian cancer provides insights into the molecular characteristics of this disease, which could help improve diagnosis and treatment.

Multi-tissue DNA methylation microarray signature is predictive of gene function

Background Transcriptional correlation networks derived from publicly available gene expression microarrays have been previously shown to be predictive of known gene functions, but less is known about the predictive capacity of correlated DNA methylation at CpG sites. Guilt-by-association co-expression methods can adapted for use with DNA methylation when a representative methylation value is created for each gene. We examine how methylation compares to expression in predicting Gene Ontology terms using both co-methylation and traditional machine learning approaches across different types of representative methylation values per gene. Methods We perform guilt-by-association gene function prediction with a suite of models called Methylation Array Network Analysis, using a network of correlated methylation values derived from over 24,000 samples. In generating the correlation matrix, the performance of different methods of collapsing probe-level data effect on the resulting gene function predictions was compared, along with the use of different regions surrounding the gene of interest. Results Using mean comethylation of a given gene to its annotated term had an overall highest prediction macro-AUC of 0.60 using mean gene body methylation, across all Gene Ontology terms. This was increased using the logistic regression approach with the highest macro-AUC of 0.82 using mean gene body methylation, compared to the naive predictor of 0.72. Conclusion Genes correlated in their methylation state are functionally related. Genes clustered in co-methylation space were enriched for chromatin state, PRC2, immune response, and development-related terms.

Methylation status of VTRNA2-1/nc886 is stable across populations, monozygotic twin pairs and in majority of tissues

Aims & methods: The aim of this study was to characterize the methylation level of a polymorphically imprinted gene, VTRNA2-1/nc886, in human populations and somatic tissues.48 datasets, consisting of more than 30 tissues and >30,000 individuals, were used. Results: nc886 methylation status is associated with twin status and ethnic background, but the variation between populations is limited. Monozygotic twin pairs present concordant methylation, whereas ∼30% of dizygotic twin pairs present discordant methylation in the nc886 locus. The methylation levels of nc886 are uniform across somatic tissues, except in cerebellum and skeletal muscle. Conclusion: The nc886 imprint may be established in the oocyte, and, after implantation, the methylation status is stable, excluding a few specific tissues.

Examining the epigenetic mechanisms of childhood adversity and sensitive periods: A gene set-based approach

BACKGROUND

Sensitive periods are developmental stages of heightened plasticity when life experiences, including exposure to childhood adversity, have the potential to exert more lasting impacts. Epigenetic mechanisms, including DNA methylation (DNAm), may provide a pathway through which adversity induces long-term biological changes. DNAm shifts may be more likely to occur during sensitive periods, especially within genes that regulate the timing of sensitive periods. Here, we investigated the possibility that childhood adversity during specific life stages is associated with DNAm changes in genes known to regulate the timing and duration of sensitive periods.

METHODS

Genome-wide DNAm profiles came from the Avon Longitudinal Study of Parents and Children (n = 785). We first used principal component analysis (PCA) to summarize DNAm variation across 530 CpG sites mapped to the promoters of 58 genes previously-identified as regulating sensitive periods. Gene-level DNAm summaries were calculated for genes regulating sensitive period opening (n_genes = 15), closing (n_genes = 36), and expression (n_genes = 8). We then performed linear discriminant analysis (LDA) to test associations between seven types of parent-reported, time-varying measures of exposure to childhood adversity and DNAm principal components. To our knowledge, this is the first time LDA has been applied to analyze functionally grouped DNAm data to characterize associations between an environmental exposure and epigenetic differences.

RESULTS

Suggestive evidence emerged for associations between sexual or physical abuse as well as financial hardship during middle childhood, and DNAm of genetic pathways regulating sensitive period opening and expression. However, no statistically significant associations were identified after multiple testing correction.

CONCLUSIONS

Our gene set-based method combining PCA and LDA complements epigenome-wide approaches. Although our results were largely null, these findings provide a proof-of-concept for studying time-varying exposures and gene- or pathway-level epigenetic modifications.

Interplays of glucose metabolism and KRAS mutation in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and deadliest cancer worldwide. The primary reasons for this are the lack of early detection methods and targeted therapy. Emerging evidence highlights the metabolic addiction of cancer cells as a potential target to combat PDAC. Oncogenic mutations of KRAS are the most common triggers that drive glucose uptake and utilization via metabolic reprogramming to support PDAC growth. Conversely, high glucose levels in the pancreatic microenvironment trigger genome instability and de novo mutations, including KRAS^G12D, in pancreatic cells through metabolic reprogramming. Here, we review convergent and diverse metabolic networks related to oncogenic KRAS mutations between PDAC initiation and progression, emphasizing the interplay among oncogenic mutations, glucose metabolic reprogramming, and the tumor microenvironment. Recognizing cancer-related glucose metabolism will provide a better strategy to prevent and treat the high risk PDAC population.

Applications of massively parallel sequencing in forensic genetics

Massively parallel sequencing, also referred to as next-generation sequencing, has positively changed DNA analysis, allowing further advances in genetics. Its capability of dealing with low quantity/damaged samples makes it an interesting instrument for forensics. The main advantage of MPS is the possibility of analyzing simultaneously thousands of genetic markers, generating high-resolution data. Its detailed sequence information allowed the discovery of variations in core forensic short tandem repeat loci, as well as the identification of previous unknown polymorphisms. Furthermore, different types of markers can be sequenced in a single run, enabling the emergence of DIP-STRs, SNP-STR haplotypes, and microhaplotypes, which can be very useful in mixture deconvolution cases. In addition, the multiplex analysis of different single nucleotide polymorphisms can provide valuable information about identity, biogeographic ancestry, paternity, or phenotype. DNA methylation patterns, mitochondrial DNA, mRNA, and microRNA profiling can also be analyzed for different purposes, such as age inference, maternal lineage analysis, body-fluid identification, and monozygotic twin discrimination. MPS technology also empowers the study of metagenomics, which analyzes genetic material from a microbial community to obtain information about individual identification, post-mortem interval estimation, geolocation inference, and substrate analysis. This review aims to discuss the main applications of MPS in forensic genetics.

Genome-wide DNA methylation profiling of stomach cancer in the ethnic population of Mizoram, North East India

Stomach cancer is the fifth most common cancer in terms of prevalence and incidence and the fourth leading cause of mortality in men and women worldwide. It is well-established that aberrant DNA methylation in cells can lead to carcinogenesis. The primary objective of our study was to investigate the aberrant DNA methylation status of genes associated with stomach cancer with a particular reference to the ethnic population of Mizoram, North East India. The site-level analysis identified 2883 CpG sites differentially methylated, representing ~922 genes. Out of which 476 Differentially Methylated Positions (DMPs) were promoter-associated, 452 DMPs were hypermethylated, and 24 were hypomethylated. The region-level analysis identified 462 Differentially Methylated Regions (DMRs) corresponding to ~320 genes, of which ~281 genes were hypermethylated and ~ 40 genes were hypomethylated. TCGA analysis showed that some of the genes had been previously implicated in other cancers including stomach cancer. Five hypermethylated genes were selected as candidate genes for further investigations and they have shown to be novel and could serve as candidate hypermethylation biomarkers for stomach cancer in this particular ethnic group.

Tissue- and ethnicity-independent hypervariable DNA methylation states show evidence of establishment in the early human embryo

We analysed DNA methylation data from 30 datasets comprising 3474 individuals, 19 tissues and 8 ethnicities at CpGs covered by the Illumina450K array. We identified 4143 hypervariable CpGs ('hvCpGs') with methylation in the top 5% most variable sites across multiple tissues and ethnicities. hvCpG methylation was influenced but not determined by genetic variation, and was not linked to probe reliability, epigenetic drift, age, sex or cell heterogeneity effects. hvCpG methylation tended to covary across tissues derived from different germ-layers and hvCpGs were enriched for proximity to ERV1 and ERVK retrovirus elements. hvCpGs were also enriched for loci previously associated with periconceptional environment, parent-of-origin-specific methylation, and distinctive methylation signatures in monozygotic twins. Together, these properties position hvCpGs as strong candidates for studying how stochastic and/or environmentally influenced DNA methylation states which are established in the early embryo and maintained stably thereafter can influence life-long health and disease.

CancerNet: a unified deep learning network for pan-cancer diagnostics

Background

Despite remarkable advances in cancer research, cancer remains one of the leading causes of death worldwide. Early detection of cancer and localization of the tissue of its origin are key to effective treatment. Here, we leverage technological advances in machine learning or artificial intelligence to design a novel framework for cancer diagnostics. Our proposed framework detects cancers and their tissues of origin using a unified model of cancers encompassing 33 cancers represented in The Cancer Genome Atlas (TCGA). Our model exploits the learned features of different cancers reflected in the respective dysregulated epigenomes, which arise early in carcinogenesis and differ remarkably between different cancer types or subtypes, thus holding a great promise in early cancer detection.

Results

Our comprehensive assessment of the proposed model on the 33 different tissues of origin demonstrates its ability to detect and classify cancers to a high accuracy (> 99% overall F-measure). Furthermore, our model distinguishes cancers from pre-cancerous lesions to metastatic tumors and discriminates between hypomethylation changes due to age related epigenetic drift and true cancer.

Conclusions

Beyond detection of primary cancers, our proposed computational model also robustly detects tissues of origin of secondary cancers, including metastatic cancers, second primary cancers, and cancers of unknown primaries. Our assessment revealed the ability of this model to characterize pre-cancer samples, a significant step forward in early cancer detection. Deployed broadly this model can deliver accurate diagnosis for a greatly expanded target patient population.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04783-y.

DNA methylation profiling of central nervous system hemangioblastomas identifies two distinct subgroups

Hemangioblastomas (HBs) of the central nervous system are highly vascular neoplasms that occur sporadically or as a manifestation of von Hippel–Lindau (VHL) disease. Despite their benign nature, HBs are clinically heterogeneous and can be associated with significant morbidity due to mass effects of peritumoral cysts or tumor progression. Underlying molecular factors involved in HB tumor biology remain elusive. We investigated genome‐wide DNA methylation profiles and clinical and histopathological features in a series of 47 HBs from 42 patients, including 28 individuals with VHL disease. Thirty tumors occurred in the cerebellum, 8 in the brainstem and 8 HBs were of spinal location, while 1 HB was located in the cerebrum. Histologically, 12 HBs (26%) belonged to the cellular subtype and exclusively occurred in the cerebellum, whereas 35 HBs were reticular (74%). Unsupervised clustering and dimensionality reduction of DNA methylation profiles revealed two distinct subgroups. Methylation cluster 1 comprised 30 HBs of mainly cerebellar location (29/30, 97%), whereas methylation cluster 2 contained 17 HBs predominantly located in non‐cerebellar compartments (16/17, 94%). The sum of chromosomal regions being affected by copy‐number alterations was significantly higher in methylation cluster 1 compared to cluster 2 (mean 262 vs. 109 Mb, p = 0.001). Of note, loss of chromosome 6 occurred in 9/30 tumors (30%) of methylation cluster 1 and was not observed in cluster 2 tumors (p = 0.01). No relevant methylation differences between sporadic and VHL‐related HBs or cystic and non‐cystic HBs could be detected. Deconvolution of the bulk DNA methylation profiles revealed four methylation components that were associated with the two methylation clusters suggesting cluster‐specific cell‐type compositions. In conclusion, methylation profiling of HBs reveals 2 distinct subgroups that mainly associate with anatomical location, cytogenetic profiles and differences in cell type composition, potentially reflecting different cells of origin.

DNA methylation may affect beef tenderness through signal transduction in Bos indicus

BACKGROUND

Beef tenderness is a complex trait of economic importance for the beef industry. Understanding the epigenetic mechanisms underlying this trait may help improve the accuracy of breeding programs. However, little is known about epigenetic effects on Bos taurus muscle and their implications in tenderness, and no studies have been conducted in Bos indicus.

RESULTS

Comparing methylation profile of Bos indicus skeletal muscle with contrasting beef tenderness at 14 days after slaughter, we identified differentially methylated cytosines and regions associated with this trait. Interestingly, muscle that became tender beef had higher levels of hypermethylation compared to the tough group. Enrichment analysis of predicted target genes suggested that differences in methylation between tender and tough beef may affect signal transduction pathways, among which G protein signaling was a key pathway. In addition, different methylation levels were found associated with expression levels of GNAS, PDE4B, EPCAM and EBF3 genes. The differentially methylated elements correlated with EBF3 and GNAS genes overlapped CpG islands and regulatory elements. GNAS, a complex imprinted gene, has a key role on G protein signaling pathways. Moreover, both G protein signaling pathway and the EBF3 gene regulate muscle homeostasis, relaxation, and muscle cell-specificity.

CONCLUSIONS

We present differentially methylated loci that may be of interest to decipher the epigenetic mechanisms affecting tenderness. Supported by the previous knowledge about regulatory elements and gene function, the methylation data suggests EBF3 and GNAS as potential candidate genes and G protein signaling as potential candidate pathway associated with beef tenderness via methylation.

Age-Related DNA Methylation in Normal Kidney Tissue Identifies Epigenetic Cancer Risk Susceptibility Loci in the ANKRD34B and ZIC1 Genes

Both age-dependent and age-independent alteration of DNA methylation in human tissues are functionally associated with the development of many malignant and non-malignant human diseases. TCGA-KIRC data were biometrically analyzed to identify new loci with age-dependent DNA methylation that may contribute to tumor risk in normal kidney tissue. ANKRD34B and ZIC1 were evaluated as candidate genes by pyrosequencing of 539 tissues, including 239 normal autopsy, 157 histopathologically tumor-adjacent normal, and 143 paired tumor kidney samples. All candidate CpG loci demonstrated a strong correlation between relative methylation levels and age (R = 0.70−0.88, p < 2 × 10−16) and seven out of 10 loci were capable of predicting chronological age in normal kidney tissues, explaining 84% of the variance (R = 0.92). Moreover, significantly increased age-independent methylation was found for 9 out of 10 CpG loci in tumor-adjacent tissues, compared to normal autopsy tissues (p = 0.001−0.028). Comparing tumor and paired tumor-adjacent tissues revealed two patient clusters showing hypermethylation, one cluster without significant changes in methylation, and a smaller cluster demonstrating hypomethylation in the tumors (p < 1 × 10−10). Taken together, our results show the presence of additional methylation risk factors besides age for renal cancer in normal kidney tissue. Concurrent tumor-specific hypermethylation suggests a subset of these loci are candidates for epigenetic renal cancer susceptibility.